AI / Full-Stack Engineer Generative Design
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Summary
Build the core intelligence behind UNLOCKLAND's AI operating system for real estate development and urban planning: LLM-powered user interaction, generative development algorithms, and geometry/spatial systems. You'll work in Python and/or TypeScript, with LLM orchestration, RAG, and computational geometry in a fast-moving Singapore startup.
About UNLOCKLAND
UNLOCKLAND is a Singapore-based AI technology company building an
AI operating system for real estate development and urban planning
.
Our platform helps real estate professionals analyse land, planning requirements, development potential and project feasibility — and generate development options across different real estate asset types. We are part of the
Harvard Innovation Labs ecosystem
, with several key enterprise customers internationally. We are expanding our AI and product engineering team in Singapore. The Role
We're looking for an engineer to help build the
core intelligence and generative systems behind UNLOCKLAND
. This is not a traditional full-stack role. A major part of your work will be developing systems that can understand a development site, interact with users through LLMs, interpret planning and design requirements, and generate viable development solutions across different asset types. These may include: Residential · Mixed-use · Office · Retail · Industrial · Hospitality · Master Planning You'll work closely with architects, urban planners, product designers and AI engineers to translate real-world development and design logic into scalable software systems. The challenge is not simply to generate geometry. It is to build systems that understand: What the user wants → What can be built → What should be generated → Why the solution makes sense.
What You'll Build1. Generative Development Algorithms
Design and implement algorithms that generate development solutions based on: Site geometry and constraints Planning and zoning requirements Setbacks and development controls Height and density constraints GFA / FAR / FSR requirements Building footprints and massing Building orientation and placement Circulation and access Unit / program mix Parking and amenities Asset-specific design requirements Commercial and development objectives You'll help build different generation strategies for different asset classes rather than relying on one generic algorithm. 2. LLM-Powered User Interaction
Build AI systems that allow users to communicate development intentions naturally. For example, a user might ask: 'Create a residential development that maximises sellable area while maintaining good unit efficiency.'
or: 'Show me three mixed-use development scenarios with different residential and retail ratios.'
Your job is to help build the system that can: understand intent → structure requirements → identify missing information → interact with the user → call the appropriate tools/algorithms → generate options → explain the results. This may involve: LLM orchestration Structured outputs Tool calling Agentic workflows Context management RAG / knowledge retrieval Planning and regulatory data Validation and guardrails Evaluation systems 3. Design → Engineering
Work closely with our AI Product Designers to turn ambitious product concepts into production-quality software. Our designers may use Figma and vibe coding to rapidly prototype new experiences. You will take those concepts and determine: How should this actually work What architecture should we use What should be deterministic vs LLM-driven What needs a geometry engine or optimisation algorithm How do we make it reliable and scalable You should enjoy turning fast-moving prototypes into robust products. 4. Geometry & Spatial Intelligence
Depending on your background, you may work on: Computational geometry Geospatial analysis Parcel and site processing Building massing generation Spatial optimisation Constraint solving Parametric generation 2D/3D geometry GIS Map-based interfaces Design option generation and evaluation Experience in architecture or computational design is helpful, but
not required
if you are a strong engineer who enjoys solving spatial problems. What We're Looking For
3+ years of software engineering experience Strong Python and/or TypeScript/JavaScript Experience building production software Hands-on experience building products with
LLMs Experience integrating LLMs into real product workflows rather than only building simple chatbots Strong understanding of APIs, databases and modern web architectures Comfortable designing algorithms and solving ambiguous technical problems Able to work closely with product designers and domain experts Strong product mindset Comfortable working in a fast-moving startup environment Strong Advantages
Experience in any of the following would be particularly valuable: Computational geometry Generative design GIS / geospatial systems Optimisation / constraint solving Architecture / AEC software CAD / BIM Three.js / WebGL Mapbox / Cesium Rhino / Grasshopper Revit / Autodesk APIs Agentic AI systems RAG / knowledge systems LLM evaluation and observability You do
not
need experience in all of these. We care more about whether you can understand complex problems and build working systems. How We Work
We work closely across disciplines: Urban Planner / Architect defines how real development and planning workflows should work ↓ AI Product Designer turns those workflows into intuitive AI-native product experiences ↓ AI / Full-Stack Engineer turns those concepts into reliable algorithms, AI systems and production software You won't just receive tickets. You'll be expected to understand the problem, challenge assumptions, propose technical approaches, prototype quickly and help shape the product. Who This Role Is For
We're looking for engineers who are excited by problems where there isn't an obvious Stack Overflow answer. For example: Given an irregular parcel, planning constraints, target GFA, building typology and commercial objectives —
how should an AI system generate and evaluate development options
Or: When should an LLM make a decision, when should it call a deterministic algorithm, and when should it ask the user for more information
Or: How do we turn an architect's design logic into an algorithm that can generate thousands of viable development scenarios
If these problems sound interesting, we'd love to talk.
UNLOCKLAND is a Singapore-based AI technology company building an
AI operating system for real estate development and urban planning
.
Our platform helps real estate professionals analyse land, planning requirements, development potential and project feasibility — and generate development options across different real estate asset types. We are part of the
Harvard Innovation Labs ecosystem
, with several key enterprise customers internationally. We are expanding our AI and product engineering team in Singapore. The Role
We're looking for an engineer to help build the
core intelligence and generative systems behind UNLOCKLAND
. This is not a traditional full-stack role. A major part of your work will be developing systems that can understand a development site, interact with users through LLMs, interpret planning and design requirements, and generate viable development solutions across different asset types. These may include: Residential · Mixed-use · Office · Retail · Industrial · Hospitality · Master Planning You'll work closely with architects, urban planners, product designers and AI engineers to translate real-world development and design logic into scalable software systems. The challenge is not simply to generate geometry. It is to build systems that understand: What the user wants → What can be built → What should be generated → Why the solution makes sense.
What You'll Build1. Generative Development Algorithms
Design and implement algorithms that generate development solutions based on: Site geometry and constraints Planning and zoning requirements Setbacks and development controls Height and density constraints GFA / FAR / FSR requirements Building footprints and massing Building orientation and placement Circulation and access Unit / program mix Parking and amenities Asset-specific design requirements Commercial and development objectives You'll help build different generation strategies for different asset classes rather than relying on one generic algorithm. 2. LLM-Powered User Interaction
Build AI systems that allow users to communicate development intentions naturally. For example, a user might ask: 'Create a residential development that maximises sellable area while maintaining good unit efficiency.'
or: 'Show me three mixed-use development scenarios with different residential and retail ratios.'
Your job is to help build the system that can: understand intent → structure requirements → identify missing information → interact with the user → call the appropriate tools/algorithms → generate options → explain the results. This may involve: LLM orchestration Structured outputs Tool calling Agentic workflows Context management RAG / knowledge retrieval Planning and regulatory data Validation and guardrails Evaluation systems 3. Design → Engineering
Work closely with our AI Product Designers to turn ambitious product concepts into production-quality software. Our designers may use Figma and vibe coding to rapidly prototype new experiences. You will take those concepts and determine: How should this actually work What architecture should we use What should be deterministic vs LLM-driven What needs a geometry engine or optimisation algorithm How do we make it reliable and scalable You should enjoy turning fast-moving prototypes into robust products. 4. Geometry & Spatial Intelligence
Depending on your background, you may work on: Computational geometry Geospatial analysis Parcel and site processing Building massing generation Spatial optimisation Constraint solving Parametric generation 2D/3D geometry GIS Map-based interfaces Design option generation and evaluation Experience in architecture or computational design is helpful, but
not required
if you are a strong engineer who enjoys solving spatial problems. What We're Looking For
3+ years of software engineering experience Strong Python and/or TypeScript/JavaScript Experience building production software Hands-on experience building products with
LLMs Experience integrating LLMs into real product workflows rather than only building simple chatbots Strong understanding of APIs, databases and modern web architectures Comfortable designing algorithms and solving ambiguous technical problems Able to work closely with product designers and domain experts Strong product mindset Comfortable working in a fast-moving startup environment Strong Advantages
Experience in any of the following would be particularly valuable: Computational geometry Generative design GIS / geospatial systems Optimisation / constraint solving Architecture / AEC software CAD / BIM Three.js / WebGL Mapbox / Cesium Rhino / Grasshopper Revit / Autodesk APIs Agentic AI systems RAG / knowledge systems LLM evaluation and observability You do
not
need experience in all of these. We care more about whether you can understand complex problems and build working systems. How We Work
We work closely across disciplines: Urban Planner / Architect defines how real development and planning workflows should work ↓ AI Product Designer turns those workflows into intuitive AI-native product experiences ↓ AI / Full-Stack Engineer turns those concepts into reliable algorithms, AI systems and production software You won't just receive tickets. You'll be expected to understand the problem, challenge assumptions, propose technical approaches, prototype quickly and help shape the product. Who This Role Is For
We're looking for engineers who are excited by problems where there isn't an obvious Stack Overflow answer. For example: Given an irregular parcel, planning constraints, target GFA, building typology and commercial objectives —
how should an AI system generate and evaluate development options
Or: When should an LLM make a decision, when should it call a deterministic algorithm, and when should it ask the user for more information
Or: How do we turn an architect's design logic into an algorithm that can generate thousands of viable development scenarios
If these problems sound interesting, we'd love to talk.
